Browse > Article
http://dx.doi.org/10.5391/JKIIS.2004.14.4.493

Multi-Stage Path Planning Based on Shape Reasoning and Geometric Search  

Hwang, Yong-K. (정보통신대학교 디지털 미디어 랩)
Cho, Kyoung-R. (동서울대학 기계공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.14, no.4, 2004 , pp. 493-498 More about this Journal
Abstract
A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.
Keywords
경로 계획;정량적 형상 추론;서비스 로봇;주행;
Citations & Related Records
연도 인용수 순위
  • Reference
1 K. K. Gupta, "A 7-dof practical motion planner based on sequential framework: theory and experiments," IEEE Int. Symp. on Assembly and Task Planning, pp. 213-218, Pittsburgh, PA, 1995.
2 Kamal Gupta and Angel P. Del Pobil, "Practical Motion Planning in Robotics Current Approaches and Future Directions," John Wiley & Sons, Chichester New York, 1998.
3 Y. K. Hwang and N. Ahuja, "Gross Motion Planning - A Survey," ACM Computing Surveys, vol. 24, no. 3, pp. 219-292, September 1992.   DOI
4 Y. K. Hwang and P. C. Chen, "A Heuristic and Complete Planner for the Classical Mover's Problem," Proc. of IEEE International Conference on Robotics and Automation, pp. 729-736, Nagoya, Japan, 1995
5 L. Kavraki and J. C. Latombe, "Randomized preprocessing of configuration space for fast path planning," IEEE Int.-Conf.-on Robotics and Automation, pp.-2138-2145, San Diego, CA, May 1994.
6 J. C. Latombe, "Robot motion planning," New York: Kluwer Academic Publishers. 1991.
7 P. C. Chen and Y. K. Hwang, "SANDROS: a Dynamic Graph Search Algorithm for Motion Planning," IEEE Transactions on Robotics and Automation, Vol. 14, No. 3, pp. 390-403, Feb 1998.   DOI   ScienceOn
8 Takno Asano, Tetsuo Asano, L. Guibas, J. Hershberger, and H. Imai, "Visibility-Polygon Search and Euclidean Shortest Path," 26th Symposium on Foundations of Computer Science, pp.155-164. 1985.
9 J. Barraquand and J. C. Latombe, "A Monte-Carlo Algorithm for Path Planning with Many Degrees of Freedom," Proceedings of IEEE International Conference on Robotics and Automation, pp. 1712-1717, Cincinnati, OH, 1990.
10 J. F. Canny, The complexity of motion planning, THe MIT Press, Cambridge, MA, 1988.
11 J. Lengyel, M. Reichert, B. R. Donald, and D. P. Greenberg, "Real-Time Robot Motion Planning Using Rasterizing Computer Graphics Hardware," Computer Graphics, vol. 24, no. 4, pp. 327-335, August 1990.   DOI
12 J. T. Schwartz and M. Sharir, "On the Piano Movers' Problem: II. Techniques for Computing Topological Properties of Real Algebraic Manifolds," Courant Institute of Mathematical Sciences, Report No. 39, 1981. (also in Advances in Applied Mathematics, no. 4, pp. 298-351, 1983)
13 T. Lozano-Prez, J. L. Jones, E. Mazer, P. A. O'Donnell, E. L. Grimson, P. Tournassoud, and A. Lanusse, "Handey: A Robot System that Recognizes, Plans, and Manipulates," IEEE Int. Conf. on Robotics and Automation, pp. 843-849, Raleigh, NC, 1987.
14 H. Noborio, T. Naniwa, and S. Arimoto, "A Feasible Motion Planning Algorithm for a Mobile Robot on a Quadtree Representation," Proceedings of IEEE International Conference on Robotics and Automation, pp. 327-332, Scottsdale, AZ, 1989.
15 C. Urmson and R. Simmons, "Approaches fro heuristically biasing RPT growth," Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 1178-1183, Las Vegas, Nevada, 2003.
16 L. Yang and S.M. Lavalle, "An improved randon neighborhood graph approach," Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 254-259, Washington DC, 2002.